mFaaS Features

Interactive Summary Dashboards

mTraction FaaS provides you an interactive dashboard to check the fraud status of the traffic on your app in a single view. This is mTraction FaaS’s Summary Dashboard, which provides you a quick overview of the top affected campaigns and top fraud sources on your app. Also, it tells you the top reason codes or the fraud reasons which are leading to fraud on your app.

Conversion Report & Fraud Scores

Conversion reports – High & Medium, provides you the list of the conversions affected by fraud along with their respective fraud scores. Fraud scores are given to the conversions on the basis of their cumulative reason code scores which define the probability of a conversion of being a fraudulent conversion. If the cumulative score is more than 80% then it’s taken to be affected with high level of fraud, if it is between 50% to 80% then it’s taken to be affected with medium level fraud and if less than 50% then it’s a normal conversion as per our algorithms.

TTI Report

TTI report or Time to install report gives the time difference between when the user clicked on the ad and the time when he first opened the app (the install postback is sent). Time to install is very important in identifying whether the traffic from a traffic fraud or not.
If the size of the app is significant and the TTI is very low then it signifies click injection or organic stuffing. If TTI is very high then it signifies click spamming.
Also much depends upon the ration of the installs with low and high TTI. If large volume of the installs are coming in the high TTI range then it generally is clear case of organic stuffing. mTraction FaaS not only highlights conversions with TTI fraud but also the sources adding to this kind of fraud..

Incent Fraud Report

Incent fraud report highlights if there is any incent mixing happening on the non-incent traffic type campaign. This is one of the most prevalent kind of app fraud in which the publishers mix the incentivised traffic to achieve campaign KPIs and show high conversion rate on the campaigns. traction FaaS highlights the subids providing incent traffic on the non-incent campaigns

Organic Stuffing Report

Organic stuffing report highlights the click injection and organic stuffing during the user acquisition. This happens close to 10% of the times when the user acquisition process is aggressive and is done from non-standard sources. This organic stuffing is a fraud as it is more of a cannibalising on the organic sources of traffic and hence this fraud leads to attribution of a high quality conversion to a paid source instead of a non-paid organic source.

Anonymous Installs

This tracks installs on generic and anonymous IPs. Users on anonymous networks often don’t fit a advertisers profile usually bypassing checks like geo targeting. FaaS is able to identify:

VPN IP Addresses: Fraudsters often use public accessible VPN networks for their large range of IP addresses for fake installs.

Tor Exit Nodes: Users of Tor networks typically use this for anonymity. This too can be turned into multi-ip fraud attacks.

Hosting Providers / Data Centers: These typically are reserved for hosting servers and typically not used for normal users.

Public Proxies: These are free proxies and typically publically known.

There are some legitimate users, however only a fraction of users, 2-4% use anonymous providers. Our system can highlight and block anomalies sources and/or geographies.

Geographic Matching

This tracks anomalies between click and install geographic distance. Generally users clicks and installs within a short duration and within a short distance. Our matching report homes in on mismatching geographic distance and highlights this for blacklisting.

Device Matching

There are two major ways fraud occurs at a device level:

Invalid device Ids: Our system has identified over 50+ different Id variants that is automatically filtered out from our system.

Modified device Ids: Some people are still using invalid Ids, ranging from the phone number, IMEI (which is discouraged by the industry) and hashed devices ids.

This hurts the advertiser because the same device is attributed to the advertiser multiple times. Hashing is becoming more prevalent in the industry today, we are able to match all common hashing strategies to determine if the same id has been attributed multiple times.